Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-23T14:45:59.481Z Has data issue: false hasContentIssue false
  • English
  • Français

A Simulation Model of Resistive Switching in Electrochemical Metallization Memory Cells (ECM)

Published online by Cambridge University Press:  31 January 2011

Stephan Menzel ,
Bart Klopstra ,
Carsten Kügeler ,
Ulrich Böttger ,
Georgi Staikov  and
Rainer Waser
Stephan Menzel
Affiliation:
[email protected], RWTH Aachen, Institut fuer Werkstoffe der Elektrotechnik, Aachen, Germany
Bart Klopstra
Affiliation:
[email protected], RWTH Aachen, Institut fuer Werkstoffe Elektrotechnik 2, Aachen, Germany
Carsten Kügeler
Affiliation:
[email protected], Forschungszentrum Juelich GmbH, Institut fuer Festkoerperforschung, Juelich, Germany
Ulrich Böttger
Affiliation:
[email protected], RWTH Aachen, Institut fuer Werkstoffe der Elektrotechnik, Aachen, Germany
Georgi Staikov
Affiliation:
[email protected], JARA - Fundamentals of Future Information Technology, Aachen, Germany
Rainer Waser
Affiliation:
[email protected], RWTH Aachen, Institut fuer Werkstoffe der Elektrotechnik, Aachen, Germany
Get access

Abstract

The storage principal of the Electrochemical Metallization Memory Cell is based on change of cell resistance induced by electro-chemical driven growth and rupture of a cupric or silver filament in an insulating matrix. This kind of switching was found in several materials as AgGeSe, CuGeS, silicon oxide or tungsten oxide [1].

During write operation copper or silver is oxidized at the corresponding electrode and copper or silver ions are driven out of the copper or silver anode into the insulating matrix due to the applied field, whereas the insulating matrix serves as solid electrolyte. The silver or copper ions migrate towards the cathode. At the cathode electrochemical reduction occurs, and deposition of metallic copper or silver takes place. Fast diffusion paths in the solid electrolyte matrix or preferred nucleation sites (seeds) at the boundary lead to filamentary growth. This growing cupric or silver dendrite finally reaches the anode and switches the device to a low resistance state.

Based on this switching mechanism a FEM simulation model was set up. To simplify the model space charges due to silver or copper migration are neglected. It is further assumed, that the conductivity in the solid electrolyte is only ionic. Hence, it is sufficient to solve the well-known Laplace equation to address the electric properties as well as ion migration. A “Level Set” method is used to track the boundary of the growing filament. The velocity of this boundary is proportional to the ionic current density calculated by Laplace equation. Based on this model simulations are applied to cell structures with multiple fast diffusion paths and seeds. Simulation results show that just one filament reaches the anode.

In a second step, Butler-Vollmer boundary conditions are introduced. This nonlinearity leads to an exponential dependence between switching time and switching voltage. As switching voltage increases, switching time decreases.

A simulation model capable of simulating ECM memory cells is presented. The model enables to simulate the behaviour of different cell geometries or different materials as solid electrolyte. Furthermore it gives deeper insight into the switching mechanism.

This work was supported by the European project EMMA “Emerging Materials for Mass storage Architectures” (FP6-033751).

Keywords

simulationmemoryelectrodeposition
Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 1160: Symposium H – Materials and Physics for Nonvolatile Memories , 2009 , 1160-H09-03
Copyright
Copyright © Materials Research Society 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1 Waser, R. and Aono, M., Nature Materials Materials, USA, 6 (2007) 833–840 Google Scholar
2 Schindler, C., Staikov, G., Waser, R., Applied Physics Letters 94, (2009) 72109/1–3Google Scholar
3 Kozicki, M. N., Gopalan, C., Balakrishnan, M. and Mitkova, M., IEEE Transactions on Na Nanotechnology notechnology, USA, 5 (2006) 535–44Google Scholar
4 Kuegeler, C., Nauenheim, C. N, Meier, M., Ruediger, R. and Waser, R., Proc Proceedings eedings of Non-volatile Memory Technology Symposium Symposium, (2008) 59–63 Google Scholar
5 Sethian, J. A., Proc. Natl. Acad. Sci USA, Vol.93, pp. 1591–1595 (1996)Google Scholar